The ability to direct specific advertisements to subscribers of entertainment programming and users of on-line services is dependent on identifying their product preferences and demographics. A number of techniques are being developed to identify subscriber characteristics, and are discussed in U.S. patent application Ser. No. 09/205,653, filed on Dec. 3, 1998, entitled xe2x80x9cSubscriber Characterization System,xe2x80x9d of which Charles A. Eldering and M. Lamine Sylla are the inventors, with an attorney docket number of T702, which is incorporated herein by reference but is not admitted to be prior art.
Even when subscriber characterizations can be performed, it is often the case that the television/set-top or personal computer that is receiving the programming is used by several members of a household. Given that these members of the household can have very different demographic characteristics and product preferences, it is important to be able to identify which subscriber is utilizing the system. Additionally, it would be useful to be able to utilize previous characterizations of a subscriber, once that subscriber is identified from a group of users.
For the foregoing reasons, there is a need for a subscriber identification system which can identify a subscribers in a household or business and retrieve previous characterizations.
The present invention encompasses a system for identifying a particular subscriber from a household or business.
The present invention encompasses a method and apparatus for identifying a subscriber based on their particular viewing and program selection habits. As a subscriber enters channel change commands in a video or computer system, the sequence of commands entered and programs selected are recorded, along with additional, information which can include the volume level at which a program is listened. In a preferred embodiment, this information is used to form a session data vector which can be used by a neural network to identify the subscriber based on recognition of that subscribers traits based on previous sessions.
In an alternate embodiment, the content that the subscriber is viewing, or text associated with the content, is mined to produce statistical information regarding the programming including the demographics of the target audience and the type of content being viewed. This program related information is also included in the session data vector and is used to identify the subscriber.
In one embodiment, subscriber selection data are processed using a Fourier transform to obtain a signature for each session profile wherein the session profile comprises a probabilistic determination of the subscriber demographic data and the program characteristics. In a preferred embodiment a classification system is used to cluster the session profiles wherein the classification system groups the session profiles having highly correlated signatures and wherein a group of session profiles is associated with a common identifier derived from the signatures.
In a preferred embodiment, the system identifies a subscriber by correlating a processed version of the subscriber selection data with the common identifiers of the subscriber profiles stored in the system.